Projects.

European Merger

At an international oil company, I was part of the McKinsey program office that merged 10 European operating units into a single business entity. My responsibilities included that staff could apply for positions in the new org structure that spanned 10 countries, as it was being built. I also oversaw the migration of 6,000 personnel, IT, and financial data into a new system. This process required a keen eye for detail, as errors were not acceptable.

Resource Allocation

At another international oil company, a staff shortage occurred due to illness, a lack of available skills in the local market, and parental leave, leading to problems with outstanding project work.

One of the main challenges in large companies is accurately counting the headcount, as there are various types of employees, contractors, temps, and service providers. Furthermore, there was no clear overview of outstanding project work as the scope was divided across six different planning and ERP systems, and ownership was shared among partners.

To tackle this issue, our company developed AI technology to consolidate all data sources, identify staff members and their project work, and optimise resource allocation to complete projects efficiently. This approach delivered four significant benefits:

For the first time there was a single view of all work and staff
Resource allocation optimisation freed up 15% of the staff to dedicate to other projects
Data in planning systems improved - especially in the details. This prevented many problems that would have otherwise occurred in the execution phase.
The client saved cost and was able to liquidate much more work in the same amount of time.

Offshore Turnarounds

Effective execution of work offshore requires meticulous planning. In addition to scheduling personnel, considerations such as deck space, power supply, and catering must be taken into account, particularly for helicopter, boat, and platform usage. In my program, we successfully executed 6,000 jobs across 50 facilities in 100 turnarounds, which required a total of 230,000 manhours by 1,200 individuals. The work was prepared and completed by over 20 different companies, necessitating a significant coordination effort.

The key was to consolidate all data from different companies and departments into a single format and location, including engineering, logistics, materials management, power supply, stocks, scope, planning, operations, offshore manning, and bedding schedules. This allowed for cross-checking and alignment, resulting in 99% flawless execution when done prior to implementation.

My company developed technology that bridged different data sources and formats, which turned out to be a critical success factor. We were able to reduce scheduled downtime by 30% while doubling the amount of executed work hours.

Currency Risk

A Norwegian food and agriculture company faces a significant risk to their net income due to fluctuating margins that correspond with the EURNOK exchange rate. The risk is directly proportional to the company's exposure, which is determined by their forecasted import needs. To mitigate this risk, hedges can be put into place. However, the data necessary for implementing these hedges is spread across multiple sources including the ERP system and several spreadsheets with forecasts and orders from key accounts.

Many companies face the same challenge of currency risk management. By consolidating the data from different sources, we can successfully minimize this risk. The Norwegian company was able to increase their net income and AGIO, which had not been achieved in years, thanks to the measures we implemented.